High Frequency Surface Wave Radar (HFSWR) is effective for the continuous detection and tracking of ships, aircraft, icebergs and other surface targets from a shore based location. Accordingly, HFSWR is being used to enhance search and rescue activities as well as to monitor sea state, illegal immigration, drug trafficking, illegal fishing, smuggling and piracy.
An HFSWR system is installed along a coastal line and includes a directional transmitting antenna and an omni-directional receiving antenna array that are both directed towards the ocean, as well as the hardware and software needed for system operation. The transmitting antenna generates a train of electromagnetic (EM) pulses which illuminate a desired surveillance area. The receiving antenna array should preferably have high and equal gain over the entire surveillance area. Objects in the surveillance area then reflect the EM pulses towards the receiving antenna array which collects radar data. Some of the objects may be elements that must be detected (the radar signatures from these elements are referred to as “targets”) while the rest of the objects are elements that do not have to be detected (the radar signatures from these elements are referred to as “clutter” which is one type of noise in a radar system). More sophisticated pulse-coded or frequency-coded EM pulses may be used to combat range-wrap which occurs when a reflected EM pulse (in response to a previously transmitted EM pulse) is received by the receiving antenna array after subsequent EM pulses have been transmitted.
Conventionally, the collected radar data from each antenna element, or sensor, in the receiving antenna array is then preprocessed by passing the data through a bandpass filter to filter extraneous unwanted signals in the radar data, and then through a heterodyne receiver which demodulates the radar data from the RF band to an IF band where analog to digital conversion occurs. The radar data is then demodulated to the baseband where low-pass filtering and downsampling occurs. The radar data collected by the receiving antenna array is complex (i.e. has real and imaginary components). Accordingly, the downsampled radar data is also complex and each of the signal processing components required to perform the above-mentioned operations are implemented to handle complex data.
The downsampled radar data is then processed by a matched filter that has a transfer function or impulse response that is related to the transmitted EM pulse. The matched filtered radar data is then separated into segments for analysis. Each segment is known in the art as a coherent integration time (CIT) or a dwell. The matched filtered radar data in each CIT is range-aligned by noting the time at which each data point was sampled relative to the time that a preceding EM pulse was transmitted. The range-aligned data is then subjected to a combination of low-pass filtering for noise reduction and downsampling for more efficient signal processing. The output of this processing is a plurality of time series of range data where each time series is collected for a given range value. The maximum range value for which the plurality of time series is collected depends on the pulse repetition interval used in transmitting the EM pulses (i.e. the frequency at which EM pulses are transmitted).
A target is detected from range, doppler and azimuth information that is generated from the pre-processed recorded radar data. The range information is used to provide an estimate of the target's distance from the receiving antenna array. The azimuth information is used to provide an estimate of the angle of the target's location with respect to the center of the receiving antenna array, and the doppler information is used to provide an estimate of the target's radial velocity by measuring the target's doppler shift. The target's doppler shift is related to the change in frequency content of the EM pulse that is reflected by the target with respect to the original frequency content of that EM pulse.
As mentioned previously, range data is generated by noting the time at which data is sampled relative to the time at which a preceding EM pulse is transmitted. Doppler processing corresponds to the detection of a sinusoidal signal of frequency Δf at the pulse repetition period (i.e. the time between consecutive transmitted pulses in the coherent pulse train). Accordingly, doppler information is generated for a given range value by subjecting the time series obtained for that range value to filter bank processing or FFT processing. The azimuth data is conventionally obtained by digital beamforming. More specifically, the radar data at a given range cell and a given doppler cell is weighted by a complex exponential for each antenna element of the receiving antenna array and then summed across all antenna elements. The phase of the complex exponential is related to the azimuth angle, the antenna element spacing and the wavelength of the transmitted EM pulses as is well known to those skilled in the art. Beamforming gives the appearance that the antenna array is tuned to a certain region of the surveillance area defined by the azimuth value in the complex exponential weights. In this fashion, many beams may be formed to simultaneously cover the entire surveillance area.
To determine a target's range, azimuth and velocity, a detector processes the generated range, azimuth and doppler information for a given CIT. In general, the detector looks for peaks at a given cell (i.e. a data value or pixel) in a two dimensional plot known as a range-doppler plot. Target detection usually comprises comparing the amplitude in a given cell with the average amplitude in neighboring cells. The detected targets are then forwarded to a plot extractor which filters the detected targets to reject all of those detections that do not conform to the range, doppler and azimuth properties that are expected for a true target. These filtered targets are then forwarded to a tracker which associates successive detections of a given target to form a track for the target. In this fashion, the movement of a detected target may be tracked throughout the surveillance area.
The detection process is hindered by the addition of noise, which includes the clutter previously mentioned, in each cell which may result in the missed detection of a target or the false detection of noise as a target. The noise is problematic since there will be a varying noise level in different cells as well as for radar data collected in different CITs, in different sea-state conditions, during different times of day and season and at different locations. The major sources of radar noise include self-interference, such as ocean clutter, ionospheric clutter and meteoroid clutter, and external interference such as co-channel interference, atmospheric interference and impulsive noise. Self-interference results from the operation of the radar while external interference is independent of radar operation.
Ionospheric clutter is one of the most significant causes of interference and is difficult to suppress due to its target-like nature and high signal amplitude. Ionospheric clutter includes EM pulses that reflect off of the earth's ionosphere and return directly to the radar (i.e. near vertical incidence clutter), and EM pulses that bounce off of the ionosphere, reflect from the ocean and return to the radar along the reverse path (i.e. range-wrap clutter). In general, ionospheric clutter accumulates in an annular band spanning several range cells, all azimuth cells and most of the ship doppler band. These range cells correspond to the height or multiple heights of the ionospheric layers relative to the HFSWR installation site. Near vertical incidence ionospheric clutter is also characterized as being very strong, isolated in range and smeared in the doppler dimension over many milli-Hertz. During the night, ionospheric clutter is at its highest level due to the disappearance of the ionospheric D layer and the merging of the ionospheric F1 and F2 layers.
To combat range-wrap clutter, Frank complementary codes may be used as is known to those skilled in the art. Another known solution is to operate the radar system at a higher frequency that does not support sky-wave propagation. By increasing the carrier frequency of the transmitted EM pulses above the layer critical frequency, the transmitted EM pulses will penetrate through the ionospheric layers. However, this approach may decrease the performance of the radar system in detecting ships at long range due to the greater propagation loss that is incurred at higher transmission frequencies.
Ocean clutter results from EM pulses that are reflected by ocean waves that are harmonics of the radar wavelength. Two large peaks that dominate ocean clutter are referred to as Bragg lines which appear as two columns of peaks in a range-doppler plot along all range cells at doppler frequencies determined by the radar operating frequency. The Bragg lines can smear radar detection performance at their corresponding doppler frequencies. However, there is also higher order scatter, related to the sea-state, that results in additional peaks and a continuum of ocean clutter between the Bragg lines. This continuum of ocean clutter contains energy that is related to the sea-state (i.e. surface wind speed and duration) often limits the detection of small, low-speed targets such as ships.
Meteoroid clutter results from meteoroids which are small meteor particles that penetrate the Earth's atmosphere and generate ionization trails that produce transient radar returns. A transient meteoroid radar return usually appears as a large peak at a specific range. Meteoroid clutter results in an increase of the background noise level in range-doppler plots.
Co-channel interference results from both local and distant users of the HFSWR frequency band, such as television broadcasters. This interference is highly directive because it originates from spatially correlated point sources. However, due to multiple reflections in non-uniform ionospheric layers, the direction of arrival of co-channel interference is wide as can be seen from a sample of real radar data shown in FIG. 1. Co-channel interference is also range independent and occurs at specific doppler frequencies as can be seen from another sample of real radar data shown in FIG. 11a. Co-channel interference may be avoided by choosing alternate carrier frequencies for transmitting the EM pulses. However, co-channel interference from distant sources poses a more serious problem since this interference is more random in time and frequency. Furthermore, there is typically greater co-channel interference at night than during the day due to the lack of D layer absorption during the night.
Atmospheric interference is spatially white with a level that varies as a function of frequency, time of day, season and geographical location. For instance, the noise level due to atmospheric interference at the lower end of the HF band, increases about 20 dB during the night in comparison with daytime levels
Impulsive noise is due to lightning and manifests itself as a sequence of rapid pulses that are randomly distributed in time and have an amplitude with a large dynamic range. This can be seen in FIG. 2 which shows a sequence of radar EM pulse returns plotted versus transmitted EM pulse number (or pulse index) for a given range value. Impulsive noise is not spatially white and results from both local and distant storms. Impulsive noise usually occurs throughout the daily operation of an HFSWR system. Impulsive noise has a doppler spread that is relatively short in duration and may resemble a maneuvering target. Impulsive noise results in an increase in the background noise level. The frequency characteristics of impulsive noise change as a function of the intensity of local storm activity.
Self-generated clutter may be successfully reduced by using sophisticated signal processing methods developed by the inventors of the present invention and described in co-pending patent application filed concurrently herewith having Ser. No. 10/383,775 and entitled “System and Method For Spectral Generation in Radar”. However, after applying these signal processing methods, the range-doppler-azimuth data still contains external interference comprised mainly of co-channel interference and impulsive interference.
Prior art external interference cancellation techniques have exploited the directional characteristics of external interference signals. These techniques employ a main antenna or main antenna array to obtain radar data containing possible targets as well as external interference and an auxiliary antenna or an auxiliary antenna array to estimate the external interference only. However, these methods require the additional hardware of an auxiliary antenna or an auxiliary antenna array. One prior art solution to this problem involves using a receiving antenna array in which some of the array elements are used as the main antenna array and some of the array elements are used as the auxiliary array. However, this results in a main antenna array having a smaller aperture (i.e. a smaller number of antenna elements) which degrades azimuthal resolution. Accordingly, there is a need for a noise reduction system which does not require the additional hardware of an auxiliary antenna array and does not degrade the azimuthal resolution of the main antenna array.